Journal Article10.1016/J.ENVSOFT.2006.10.004
An effective screening design for sensitivity analysis of large models
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TL;DR: A revised version of the elementary effects method is proposed, improved in terms of both the definition of the measure and the sampling strategy, having the advantage of a lower computational cost.
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Abstract: In 1991 Morris proposed an effective screening sensitivity measure to identify the few important factors in models with many factors. The method is based on computing for each input a number of incremental ratios, namely elementary effects, which are then averaged to assess the overall importance of the input. Despite its value, the method is still rarely used and instead local analyses varying one factor at a time around a baseline point are usually employed. In this piece of work we propose a revised version of the elementary effects method, improved in terms of both the definition of the measure and the sampling strategy. In the present form the method shares many of the positive qualities of the variance-based techniques, having the advantage of a lower computational cost, as demonstrated by the analytical examples. The method is employed to assess the sensitivity of a chemical reaction model for dimethylsulphide (DMS), a gas involved in climate change. Results of the sensitivity analysis open up the ground for model reconsideration: some model components may need a more thorough modelling effort while some others may need to be simplified.
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Citations
Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling
Charles Rougé,Charles Rougé,Patrick M. Reed,Danielle S. Grogan,Shan Zuidema,Alexander A. Prusevich,Stanley Glidden,Jonathan R. Lamontagne,Richard B. Lammers +8 more
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Multivariate global sensitivity analysis for dynamic models based on wavelet analysis
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TL;DR: A new kind of sensitivity indices based on wavelet analysis is proposed, which contain the information of model output in both time and frequency domains and are applied to an environmental model to tell the relative importance of the input variables, which can be useful for improving the model performance.
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Performing Global Uncertainty and Sensitivity Analysis from Given Data in Tunnel Construction
TL;DR: In this article, a hybrid approach that integrates metamodeling, machine learning algorithms, and a variance decomposition technique to support global uncertainty and sensitivity is proposed to improve global sensitivity.
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‘One Size Does Not Fit All’: A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models
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TL;DR: It is argued that no single SA method fits all ABMs and that different methods of SA should be used based on the overarching purpose of the model, and a roadmap is presented that guides ABM developers through the process of performing SA that best fits the purpose of their ABM.
Global sensitivity analysis of a three-dimensional nutrients-algae dynamic model for a large shallow lake
TL;DR: In this paper, the authors applied the Morris sensitivity analysis method to identify the important factors governing the dynamics in a complex 3-dimensional water quality model, which was developed using the Environmental fluid dynamics code (EFDC) to simulate the fate and transport of nutrients and algal dynamics in Lake Dianchi.
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Factorial sampling plans for preliminary computational experiments
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Magnus Arnér
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Factorial sampling plans for preliminary computational experiments
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2.5K